We train models using the 113 video sequences that do not overlap with any of the two splits. Moreover, since our framework quickly converges, we need just a few samples to achieve state-of-the-art results; thus, we use a subset of about 6K (one every five frames) samples. Nonetheless, for a fair comparison, we retrain our supervised competitor [1]} over the whole available training set, yet avoiding overlapping with the 142 split (over which the weights released by the authors have been trained on).
